def make_train_data(root: tk.Tk, user_name: str,
image_name: str) -> (bool, str):
image_dir_path = config.path.root_image_dir_path / \
image_name/'1'
if not image_dir_path.exists():
raise MakeTrainDataException(f'{str(image_dir_path)} is not found')
elif not image_dir_path.is_dir():
raise MakeTrainDataException(f'{str(image_dir_path)} is not directory')
image_path = list(
itertools.chain(image_dir_path.glob('*.jpg'),
image_dir_path.glob('*.png')))[0]
try:
scored_param_dir_path = get_save_dir_path(
config.path.root_scored_param_dir_path, user_name, image_name)
scored_param_path = get_save_file_path(
scored_param_dir_path,
'scored_param' + DataWriter.ScoredParamWriter.SUFFIX)
except MiscException as e:
raise MakeTrainDataException(e)
sub_win = tk.Toplevel(root)
try:
compare_num = 100
is_complete = compare(sub_win, image_path, scored_param_path,
compare_num)
return is_complete, scored_param_path
except TrainDataMakerException as e:
sub_win.destroy()
raise MakeTrainDataException(e)
def score(root: Tk, user_name: str, image_name: str, image_number: str):
image_dir_path = root_image_dir_path / image_name / image_number / 'random_enhance_10'
if not image_dir_path.exists():
raise FileNotFoundError
elif not image_dir_path.is_dir():
raise NotADirectoryError
game = TournamentGame(list(map(str, image_dir_path.iterdir())),
ImageGenerator())
scored_image_dir = get_save_dir_path(root_scored_image_dir_path, user_name,
f'{image_name}/{image_number}')
scored_param_dir = get_save_dir_path(root_scored_param_dir_path, user_name,
f'{image_name}/{image_number}')
scored_param_path = get_save_file_path(scored_param_dir,
'scored_param.json')
data_writer_list = [
DW_scored_image.ScoredImageWriter(str(scored_image_dir)),
DW_scored_param.ScoredParamWriter(str(scored_param_path))
]
sub_win = Toplevel(root)
canvas = CompareCanvasGroupFrame(sub_win,
game,
data_writer_list=data_writer_list)
canvas.pack()
canvas.disp_enhanced_image()
canvas.focus_set()
sub_win.grab_set()
sub_win.wait_window()
def make_log(logbook, log_dir_path: str):
field_name_list = ['gen', 'avg', 'min', 'max']
log_dict = {key: value for key, value in zip(
field_name_list, logbook.select(*field_name_list))}
log_file_path = get_save_file_path(log_dir_path, 'fitness.json')
with open(log_file_path, 'w') as fp:
json.dump(log_dict, fp, indent=4)
def make_graph(log_file_path: str, log_dir_path: str):
with open(log_file_path, 'r') as fp:
log_dict = json.load(fp)
fig, ax1 = plt.subplots()
ax1.set_xlabel("Generation")
ax1.set_ylabel("Fitness")
ax1.plot(log_dict['gen'], log_dict['avg'],
color='r', label="Average Fitness")
ax1.plot(log_dict['gen'], log_dict['min'],
color='g', label="Minimum Fitness")
ax1.plot(log_dict['gen'], log_dict['max'],
color='b', label="Maximum Fitness")
ax1.legend()
save_file_path = get_save_file_path(log_dir_path, 'graph.png')
plt.savefig(str(save_file_path))
rightfulness_dir_path = get_save_dir_path(
root_rightfulness_dir_path, args.user_name,
f'{args.image_name}/{args.image_number}')
scored_param_list.sort(key=lambda x: x['score'], reverse=True)
for index, scored_param in enumerate(tqdm(scored_param_list)):
image = Image.open(scored_param['param'])
new_image = Image.new(image.mode, (image.width, image.height + 100),
(255, 255, 255))
new_image.paste(image, (0, 0))
draw = ImageDraw.Draw(new_image)
text_dict = {
key: f'{key:<10s}:{scored_param[key]:>5,.2f}'
for key in ['score', 'evaluate']
}
font = ImageFont.truetype(r"C:\Windows\Fonts\Arial.ttf", size=30)
draw.text((0, image.height + 30),
f'{text_dict["score"]}\n{text_dict["evaluate"]}',
fill=(0, 0, 0),
font=font)
save_file_path = get_save_file_path(rightfulness_dir_path,
f'{index:0=3}.png')
new_image.save(str(save_file_path))